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GLOSSARY
Indicators of socioeconomic position (part 1)
Bruna Galobardes, Mary Shaw, Debbie A Lawlor, John W Lynch, George Davey Smith
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J Epidemiol Community Health 2006;60:7–12. doi: 10.1136/jech.2004.023531
This glossary presents a comprehensive list of indicators of
socioeconomic position used in health research. A
description of what they intend to measure is given together
with how data are elicited and the advantages and
limitation of the indicators. The glossary is divided into two
parts for journal publication but the intention is that it
should be used as one piece. The second part highlights a
life course approach and will be published in the next issue
of the journal.
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S
See end of article for
authors’ affiliations
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Correspondence to:
Dr B Galobardes,
Department of Social
Medicine, University of
Bristol, Canynge Hall,
Whiteladies Road, Bristol
BS8 2PR, UK; bruna.
[email protected]
Accepted for publication
9 September 2004
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ocioeconomic position (SEP) is a commonly
used concept in health research. Although
researchers have an intuitive sense of what
SEP means, the numerous ways of measurement
indicate the complexity of the construct. A
variety of other terms, such as social class, social
stratification, social or socioeconomic status, are
often used interchangeably despite their different theoretical bases and, therefore, interpretations. These issues have been discussed in detail
by Krieger et al1 and we use SEP rather than
socioeconomic status in line with their suggestion. ‘‘Socioeconomic position’’ refers to the
social and economic factors that influence what
positions individuals or groups hold within the
structure of a society,1 2 and encompasses concepts with different historical and disciplinary
origins, which will briefly be reviewed here. SEP
is related to numerous exposures, resources, and
susceptibilities that may affect health. This
glossary presents a comprehensive list of indicators of SEP used in health research, together
with a description of what they intend to
measure, how data are elicited, and their main
advantages and limitations. The glossary builds
on previous work2–6 by providing updated information on the use and meaning of each measure,
specifically in relation to epidemiological and
health research.
There is no single best indicator of SEP
suitable for all study aims and applicable at all
time points in all settings. Each indicator
measures different, often related aspects of
socioeconomic stratification and may be more
or less relevant to different health outcomes and
at different stages in the life course. The choice of
SEP measure(s) should ideally be informed by
consideration of the specific research question
and the proposed mechanisms linking SEP to the
outcome. This is the case when SEP is the
exposure of interest as well as when it is being
considered as a confounding/mediating factor. If
the central interest is to show the existence of a
socioeconomic gradient in a particular health
outcome then the choice of indicator may not be
crucial. However, even in a case such as this,
using different indicators of SEP may result in
gradients of varying slopes. Furthermore, while a
single measure of SEP may show an association
with a health outcome, it will not encompass the
entirety of the effect of SEP on health. This issue
is of particular importance when SEP is a
potential confounding factor. Multiple SEP indicators, preferably measured across the life
course, will be needed to avoid residual confounding by unmeasured socioeconomic circumstances.7 12 The notion that the choice of SEP
measure should be determined by the particular
research question is exemplified by Snow’s work
on exposures related to people working in the
‘‘offensive trades’’.8 9 With respect to socially
patterned exposures that have aetiological effects
specific to particular stages of the life course it is
clear that the socioeconomic indicators should
relate to these life stages.10 Other researchers
have emphasised the importance of theoretically
grounded measures of social position in recent
contributions.11 However, in practice, the measures used tend to be driven by what is available
or has been previously collected. Even when a
researcher cannot influence the particular SEP
measure(s) available in a study, an understanding of their theoretical basis is important to
making appropriate inferences.
In this glossary we highlight the theoretical
basis, measurement, interpretation, strengths,
and limitations of each indicator. Where possible
we present the interpretation or mechanism that
may be of particular relevance to each indicator,
but this is difficult because most of these
indicators are strongly correlated. For example,
despite education reflecting some particular
aspects of SEP such as possession of a richer
score of knowledge, it does, at the same time,
help determine a person’s adult occupation and
income, and therefore shares some of the health
effects of these other indicators. This is particularly evident when a life course approach is
considered (see fig 1 and part 2 of this glossary).
Most work on health inequalities has been
conducted in developed countries and has
generated indicators appropriate to this context.
Further research is necessary to develop indicators that might be more appropriate in developing country settings. The glossary is organised
such that individual level indicators are considered first, and within this they are presented in
alphabetical order. Various forms of aggregate
indicators (composite indicators and indices of
area deprivation) follow. Finally, we briefly
discuss life course SEP and multilevel
approaches to considering SEP influences. The
glossary is divided in two parts for journal
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Galobardes, Shaw, Lawlor, et al
Childhood
Parent's education
Parent's occupation
Young adulthood
Education
Active professional life
First employment
Occupation first,..., last,
longest
Income
Retirement
Household income
Wealth, deprivation
Housewife
Household income
Household conditions
Household conditions
Assets transfer occurring
when starting a family
Household conditions
Unemployment: yes/no,
number of episodes
Income: changes over
time
Assets transfer across
generations occurring
at death
Wealth, deprivation:
changes over time
Household conditions:
changes over time
Partner's SEP
Figure 1
Examples of indicators measuring life course socioeconomic position.
publication, but the intention is that it should be used as one
piece.
THEORETICAL ORIGINS
Many of the concepts underlying the use of SEP in
epidemiological research have their origin in the work of
two social theorists, Karl Marx and Max Weber. For Marx,
SEP was entirely determined by ‘‘social class’’, whereby an
individual is defined by their relation to the ‘‘means of
production’’ (for example, factories, land). Social class, and
class relations, are characterised by the inherent conflict
between exploited workers and the exploiting capitalists or
those who control the means of production. Despite the
palpable political weight of Marxist ideology in the 20th
century we are aware of only two classifications used in
epidemiological research that are based on Marx’s theory of
social class, these are Erik Olin Wright’s classification13 and
others developed in South America.14 In contrast with Marx,
who viewed social stratification in capitalist societies as both
source and outcome of the conflict between two necessarily
opposed social groups, Weber’s theory suggests that society is
hierarchically stratified along many dimensions, creating
groups whose members share a common market position
leading to shared ‘‘life chances’’. For Weber, market position
is not necessarily only defined by Marx’s class relations. For a
more detailed summary of these sociological theories see
Bartley.15
primary or high school, higher education diplomas, or
degrees. The continuous measure assumes that every year
of education contributes similarly to a person’s attained SEP
and that time spent in education has greater importance than
educational achievements, whereas the latter assumes that
specific achievements are important in determining SEP.3
Interpretation
Although education is often used as a generic measure of
SEP, there are specific interpretations to explain its association with health outcomes3 18–20:
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EDUCATION
Theoretical basis
Education is a frequently used indicator in epidemiology. The
use of education as an SEP indicator has its historical origins
in the status domain of Weberian theory,3 and it attempts to
capture the knowledge related assets of a person.2 As formal
education is normally completed in young adulthood and is
strongly determined by parental characteristics, it can be
conceptualised within a life course framework as an indicator
that in part measures early life SEP.16 17
Measurement
Education can be measured as a continuous variable (years of
completed education), or as a categorical variable by
assessing educational milestones such as completion of
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Education captures the transition from parents’ (received)
SEP to adulthood (own) SEP and it is also a strong
determinant of future employment and income.2 17 It
reflects material, intellectual, and other resources of the
family of origin, begins at early ages, is influenced by
access to and performance in primary and secondary
school and reaches final attainment in young adulthood
for most people. Therefore it captures the long term
influences of both early life circumstances on adult health,
as well as the influence of adult resources (for example,
through employment status) on health.17 21 22
The knowledge and skills attained through education may
affect a person’s cognitive functioning, make them more
receptive to health education messages, or more able to
communicate with and access appropriate health services.
A recent attempt to measure knowledge in terms of
‘‘cultural literacy’’ and assess its role in the association
between education and health highlighted the great
difficulty in trying to unpack some of the specific ways
in which education and knowledge may affect health.23 24
Ill health in childhood could limit educational attendance
and/or attainment and predispose to adult disease,
generating a health selection influence on health inequalities.25
Strengths and limitations
Education is comparatively easy to measure in self administered questionnaires, garners a high response rate, and is
relevant to people regardless of age or working circumstances, unlike many other SEP indicators.3 In addition, the
Socioeconomic position
collection of information on education may be less contentious in some contexts than other SEP indicators such as
income.
The meaning of educational level varies for different birth
cohorts. In addition to secular trends in improving educational attainment, there have been considerable changes in
educational opportunities for women and some minority
groups over recent decades. Such cohort effects can be
important but are seldom accounted for in epidemiological
studies. The results from studies that use years of education
or educational qualifications that include participants from a
number of different birth cohorts may be biased if cohort
effects are not taken into account, because older cohorts will
be over-represented among those classified as less educated.26
There are examples of how cohort effects have been
accounted for in epidemiological studies. In one study the
authors classified participants into low, medium, or high
levels of education, these categories being defined with
specific relevance to their birth cohort.16 This will help
account for the fact that cohorts born earlier who have, in
absolute terms, fewer years of education, may be classified in
the same relative group of education than cohorts born later,
despite these having greater absolute number of years of
education. Another option is to stratify the analysis by age
group, for example examining health inequalities by educational attainment within five year age groups.27 A further
limitation of educational levels exists if individuals have
obtained their education outside the country of residence—
that is, in a different educational regime in which indicators
of education may have very different implications than
within the host country. Finally, measuring the number of
years of education or levels of attainment may contain no
information about the quality of the educational experience,
which is likely to be important if conceptualising the role of
education in health outcomes specifically related to knowledge, cognitive skills, and analytical abilities but may be less
important if education is simply used as a broad indicator of
SEP.
HOUSING TENURE, HOUSING CONDITIONS, AND
HOUSEHOLD AMENITIES
Theoretical basis
Housing characteristics measure material aspects of socioeconomic circumstances. Housing based indicators are used
in industrialised and non-industrialised countries, although
the characteristics assessed differ. Moreover, these may be
very specific to the area where they were developed. A recent
glossary presents some of these indicators.28 We mention here
those that are more directly related to SEP.
Measurement
The most commonly used characteristic is housing tenure—
whether housing is owner occupied (owned outright or being
bought with a mortgage), or rented from a private or social
landlord. In rural populations ownership of a farm and farm
size may better define housing characteristics.29
A number of household amenities are used in epidemiological
studies, including access to hot and cold water in the house,
having central heating and carpets, sole use of bathrooms
and toilets, whether the toilet is inside or outside the home,
having a refrigerator, washing machine, or telephone. These
household amenities are markers of material circumstances
and may also be associated with specific mechanisms of
disease. For example, lack of running water and a household
toilet may be associated with increased risk of infection.29 30
In addition the meaning of these amenities will vary by
context and cohort (see the example of car access below).
Very few people in contemporary advanced industrial
societies will be without running hot water, indoor toilet or
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bathroom facilities and, therefore, some of these measures
are not able to differentiate individuals in these populations.
However, these indicators or other household amenities will
have relevance in developing country populations (see
below), and as indicators of childhood SEP in older adults
in contemporary developed country populations (see for
example their use in some articles12 31 32). One amenity that
has proved to be a useful SEP indicator in the UK, but that
has been used less in other populations, is car access.33–35 In
rural areas of industrialised countries car ownership may not
be a useful indicator of SEP as even the poorest households
often own cars, out of sheer necessity.36 In non-industrialised
countries, other assets that have been used as indicators of
SEP in health related research include the number of
livestock, owning a bicycle, refrigerator, radio, sewing
machine, TV, or a clock.37–39
In addition to household amenities, household conditions
such as the presence of damp and condensation, building
materials, rooms in the dwelling, and overcrowding are
housing related indicators of material resources. These are
used in both industrialised and non-industrialised countries.40–43 Crowding is calculated as the number of persons
living in the household per number of rooms available in the
house (usually excluding kitchen and bathrooms).
Overcrowding is then defined as being above a specific
threshold (commonly two or more people per room).
Overcrowding can plausibly affect health outcomes through
a number of different mechanisms: overcrowded households
are often households with few economic resources and there
may also be a direct effect on health through facilitation of
the spread of infectious diseases.
Recent efforts to better understand the mechanisms
underlying socioeconomic inequalities in health have lead
to the development of some innovative area level indicators
that use aspects of housing. For example, a ‘‘broken windows’’
index measured housing quality, abandoned cars, graffiti,
trash, and public school deterioration at the census block
level in the USA.44 This indicator was more useful in
explaining the variance in gonorrhoea rates than a poverty
index that included income, unemployment, and low
education. Similarly, an indicator of the ‘‘social standing of
the habitat’’ combined characteristics of the building, their
immediate surroundings and the local neighbourhood of
residential buildings can be used to assign SEP.45
Concordance of this measure with education or occupation
was good for people of either high or low socioeconomic
position, but not for those with medium education and/or
occupation, showing the heterogeneity of socioeconomic
circumstances among people labelled as middle class.45
Interpretation
These indicators are mainly markers of material circumstances. Housing is generally the key component of most
people’s wealth, and accounts for a large proportion of the
outgoings from income. Housing (and its context) is an
important, multifaceted and sometimes difficult to interpret
indicator of SEP. As discussed above, some housing
characteristics may be direct exposures or markers of
exposures for specific diseases.
Strength and limitations
Housing characteristics and amenities are extensively used as
measures of SEP. They are comparatively easy to collect and
may also provide some indications of specific mechanisms
linking SEP to particular health outcomes (for example,
crowding). Their main limitation is that, although measuring
the same underlying concept, these indicators may be specific
to the temporal and geographical context where they were
developed and thus be difficult to compare across studies.
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Galobardes, Shaw, Lawlor, et al
INCOME
Theoretical basis
Income is the indicator of SEP that most directly measures
the material resources component. As with other indicators
such as education, income has a ‘‘dose-response’’ association
with health,46 47 and can influence a wide range of material
circumstances with direct implications for health.2 3 Income
also has a cumulative effect over the life course48 and is the
SEP indicator that can change most on a short term basis,
although this dynamic aspect is rarely taken into account in
epidemiological studies.49 It is implausible that money in
itself directly affects health, thus it is the conversion of
money and assets into health enhancing commodities and
services via expenditure that may be the more relevant
concept for interpreting how income affects health.
Consumption measures are, however, rarely used in epidemiological studies.
Measurement
People can either be asked to report their absolute income or
can be asked to place themselves within predefined categories. Most often income of the household rather than of
individuals is measured. While individual income will
capture individual material characteristics, household income
may be a useful indicator, in particular for women, who may
not be the main earners in the household. Using household
income information to apply to all the people in the
household assumes an even distribution of income according
to needs within the household, which may or may not be
true. For income to be comparable across households,
additional information on family size or the number of
people dependent on the reported income should be elicited.1
This can be then transformed into ‘‘equivalised income’’,47 50
which adjusts for family size and its associated costs of
living.3
Income may be measured as a relative indicator establishing levels of poverty (for example, percentage above or below
the official poverty level in a given year48).
Interpretation
Income primarily influences health through a direct effect on
material resources that are in turn mediated by more
proximal factors in the causal chain such as behaviours.
The mechanisms through which income could affect health
are:
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Buying access to better quality material resources such as
food and shelter.
Allowing access to services, which may improve health
directly (such as health services, leisure activities) or
indirectly (such as education).
Fostering self esteem and social standing by providing the
outward material characteristics relevant to participation
in society.
Reverse causality may also be considered as income level
can be affected by health status.
Strengths and limitations
Income is arguably the best single indicator of material living
standards. There is evidence that personal income is a
sensitive issue and people may be reluctant to provide such
information,51 although this may have been overstated.52 In
different settings (including different countries, different
birth cohorts, different sexes) income may be a more or less
‘‘sensitive’’ indicator (with respect to participants’ willingness to disclose this information accurately) relative to
educational attainment and occupation. Ideally we want to
be able to collect disposable income as this reflects what
individuals/households can actually spend, but often we
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collect gross incomes or incomes that do not take account of
in-kind transfers that function as hypothecated income (such
as food stamps in the USA). While income may be a sensitive
question and potentially subject to greater non-response than
other SEP questions, more sophisticated methods for eliciting
accurate income information (especially for in-person interviews) have been developed, but of course these come at a
cost of having to devote more space and time to collect these
data. The meaning of current income for different age groups
may vary and be most sensitive during the prime earning
years. Income for young and older adults may be a less
reliable indicator of their true SEP because income typically
follows a curvilinear trajectory with age.
OCCUPATION BASED MEASURES
Theoretical basis
Occupation based indicators of SEP are widely used.
Occupation can: represent Weber’s notion of SEP as a
reflection of a person’s place in society related to their social
standing, income and intellect; characterise working relations between employers and employees; or, less frequently,
characterise people as exploiters or exploited in class
relations.
Measurement
Most studies use the current or longest held occupation of a
person to characterise their adult SEP. However, with
increasing interest in the role of SEP across the life course,
some studies include parental occupation as an indicator of
childhood SEP in conjunction with individuals’ occupations
at different stages in adult life.53 Occupational measures are
in some sense transferable: measures from one individual, or
combinations of several individuals, can be used to characterise the SEP of others connected to them. For example,
the occupation of the ‘‘head of the household’’, or the
‘‘highest status occupation in the household’’, can be used as
an indicator of the SEP of dependants (for example, spouse,
children) or the household as a unit.
Interpretation
Different occupational classification schemes measure particular aspects of SEP, although it may be difficult to
disentangle the specific effects of individual indicators.
Some of the more general mechanisms that may explain
the association between occupation and health related
outcomes are presented here (for each classification we
highlight the specific aspect it focuses on):
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Occupation (parental or own adult) is strongly related to
income and therefore the association with health may be
one of a direct relation between material resources—the
monetary and other tangible rewards for work that
determines material living standards—and health.
Occupations reflect social standing and may be related to
health outcomes because of certain privileges—such as
easier access to better health care, access to education, and
more salubrious residential facilities—that are afforded to
those of higher standing.
Occupation may reflect social networks, work based stress,
control, and autonomy and thereby affect health outcomes
through psychosocial processes.
Occupation may also reflect specific toxic environmental
or work task exposures such as physical demands (for
example, transport driver, labourer).
Strengths and limitations
An important strength of these measures is their availability
in many routine data sources, including census data and on
death certificates. One of the most important limitations of
Socioeconomic position
occupational indicators is that they cannot be readily
assigned to people who are not currently employed. As a
result, if used as the only source of information on SEP,
socioeconomic differentials may be underestimated through
the exclusion of some of the population.54 Groups commonly
excluded are retired people, people whose work is inside the
home (mainly affecting women), the unemployed, students,
and people working in unpaid, informal, or illegal jobs.
Although previous occupation can be assigned to those who
are retired and to some unemployed people, and husband’s
occupation is often used to assign women’s SEP, this may
inadequately
index
current
social
circumstances.
Furthermore, other groups are less readily defined or willing
to disclose their ‘‘occupation’’. People who are self employed
can be difficult to classify, for example it is unclear in some
occupationally based classifications whether someone who is
a self employed builder with a team of 20 workers working
for her is classified as a manager or a skilled manual worker.
Some contemporary classification systems (see part 2)
operationalise the classification of the self employed in a
more meaningful way.
As with education, occupation may have different meanings for different birth cohorts and in different geographical
settings (which may make international comparisons problematic). For example, for older generations the allocation of a
husband’s occupation to define a woman’s SEP may have
been appropriate and acceptable, but this is unlikely to be the
case for many contemporary working populations where the
participation rates of women, and their expectations of
recognition, are much higher. Cohort influences are also
relevant in terms of the changing structure and composition
of the workforce—in industrialised societies fewer contemporary school leavers go into unskilled or semi-skilled
occupations, whereas computer or IT based occupations are
increasingly common. Additionally, the exposure consequences of working in different jobs may change with the
advent of stricter occupational health legislation and new
technologies that eliminate toxic exposures.
The second part of the glossary continues by describing
specific occupation based indicators.
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Authors’ affiliations
B Galobardes, M Shaw, D A Lawlor, G Davey Smith, Department of
Social Medicine, University of Bristol, Bristol, UK
M Shaw, South West Public Health Observatory, UK
J W Lynch, Department of Epidemiology, School of Public Health and
Center for Social, Epidemiology and Population Health, University of
Michigan, USA
Funding: The work of JWL and GDS is supported (in part) by a Robert
Wood Johnson Foundation Investigators Award in Health Policy
Research. Funds from this award also partly support BG. MS is funded
by the South West Public Health Observatory. DAL is funded by a UK
Career Scientist Award. The views expressed in this paper are those of
the authors and not necessarily any funding bodies.
Conflicts of interest: none declared.
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ECHO . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Evaluation of the National Congenital Anomaly System in England and Wales
T Misra, N Dattani, A Majeed
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this article.
Objective: To evaluate the National Congenital Anomaly System (NCAS).
Methods: The NCAS in England and Wales based at the Office for National Statistics and the
various regional registers that exchange data with it were examined, based on guidelines for
evaluating public health surveillance systems, published by the Centres for Disease Control
(CDC). Data relating to congenital anomaly notifications received from 1991 to 2002 were
analysed.
Main outcome measures: The main outcome measures were based on CDC standards and
included the level of usefulness of the system, simplicity, flexibility, data quality,
acceptability, sensitivity, representativeness, timeliness, and stability of the system.
Results: The NCAS has two main tiers: the "passive" system of voluntary notifications and
the anomaly registers, but many reporting sources within these. It receives about 7000
notifications a year. It is inflexible and has variable data quality. The voluntary nature of
reporting affects the system’s acceptability. The sensitivity as compared with two regional
registers (Trent and Wales) is about 33%. The congenital anomaly registers reporting to the
NCAS achieve high levels of coverage and completeness. From 2003, they cover 42% of all
births and account for the major proportion of the notifications.
Conclusions: The NCAS serves the important function of monitoring birth defects in
England and Wales, but is not currently operating in a timely or effective way. It should be
adapted to meet its main objectives more effectively. More regional anomaly registers
should be instituted and existing registers supported through central funds.
m Archives of Disease in Childhood Fetal and Neonatal Edition 2005;90:F368–F373.
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